Bulletin of the Chinese Ceramic Society, Volume. 41, Issue 1, 118(2022)

Comprehensive Performance Prediction of Concrete Based on Relevance Vector Machine Model

ZHANG Yan1,2, WANG Pengpeng2, and WU Zhekang2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    References(6)

    [3] [3] SHAMSUDIN M M H, HAMID N H, FAUZI M A M. Compressive and flexural strength of concrete containing recycled polyethylene terephthalate (PET)[J]. Key Engineering Materials, 2021, 879: 13-21.

    [10] [10] ELHAKIM A F, EL KHOULY M A A, AWAD R. Three dimensional modeling of laterally loaded pile groups resting in sand[J]. HBRC Journal, 2016, 12(1): 78-87.

    [12] [12] CHEN S Y, GU C S, LIN C N, et al. Multi-kernel optimized relevance vector machine for probabilistic prediction of concrete dam displacement[J]. Engineering With Computers, 2021, 37(3): 1943-1959.

    [13] [13] TIPPING M E. Escaping the convex hull with extrapolated vector machines[M]//Advances in Neural Information Processing Systems 14. The MIT Press, 2002: 652-658.

    [16] [16] DEO R C, SAMUI P, KIM D. Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models[J]. Stochastic Environmental Research and Risk Assessment, 2016, 30(6): 1769-1784.

    [17] [17] CAMPS-VALLS G, MARTINEZ-RAMON M, ROJO-ALVAREZ J L, et al. Nonlinear system identification with composite relevance vector machines[J]. IEEE Signal Processing Letters, 2007, 14(4): 279-282.

    Tools

    Get Citation

    Copy Citation Text

    ZHANG Yan, WANG Pengpeng, WU Zhekang. Comprehensive Performance Prediction of Concrete Based on Relevance Vector Machine Model[J]. Bulletin of the Chinese Ceramic Society, 2022, 41(1): 118

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Aug. 11, 2021

    Accepted: --

    Published Online: Aug. 4, 2022

    The Author Email:

    DOI:

    CSTR:32186.14.

    Topics